10 Prompts for Claude: How AI Replaces Expensive Market Analysts
The analytics market is undergoing a tectonic shift. There is no longer a need to hire expensive consultants or pay for premium research—artificial intelligence is taking over the functions of a full-service analyst. A set of 10 specialized prompts for Claude has been published, enabling deep fundamental analysis of companies and cryptocurrencies at the level of leading consulting firms.
These queries do not provide trading recommendations—they structure the research process, replacing an entire department of analysts. Each prompt assigns Claude a specific role and a set of parameters for analysis, covering the full cycle: from a general business overview to a detailed assessment of risks and management quality.
The First Five: From Overview to Valuation
The first prompt turns Claude into a senior analyst who prepares a beginner-friendly research report on a company or ticker. It covers the business model, revenue sources, industry trends, competitors, financial results, valuation, growth drivers, and bull/base/bear scenarios. The query requires reliance on recent public sources, specifying dates and clearly separating facts from assumptions.
The second prompt breaks down the company's latest earnings call: five key takeaways, changes in revenue and margins, management guidance, management tone, analyst concerns, pleasant and unpleasant surprises. It also generates a table of key metrics with current and previous results, along with an explanation of why each matters.
The third query assigns Claude the role of a skeptical analyst who looks for red flags in revenue quality, margins, cash flow, debt, dilution, insider actions, and management language. Each issue is assigned a severity rating, and a final risk score from 1 to 10 is given.
The fourth and fifth prompts focus on competitive advantages and valuation. One assesses the company's "moat"—brand, network effects, switching costs, scale, intellectual property—on a scale and compares it with competitors. The second compares the company with peers using multiples (P/E, forward P/E, EV/revenue, EV/EBITDA) and explains whether it appears cheap, fairly valued, or expensive.
The Second Five: From DCF Model to a Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model—a method for valuing a company based on future earnings. It generates bear, base, and bull scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, explaining the logic behind each assumption.
The seventh query creates a catalyst calendar for 3, 6, and 12 months: earnings reports, product launches, investor days, regulatory decisions, lawsuits, macro events, management changes, buybacks, and dividends. For each event, it specifies timing, impact, upside and downside risks, confidence level, and source.
The eighth prompt evaluates the management team: the CEO's track record, the CFO's credibility, forecast accuracy, transparency, capital allocation, acquisitions, insider ownership size, and compensation. The ninth query simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and a neutral judge explains which position is better supported.
The tenth prompt turns Claude into a patient teacher who explains the company in simple terms: what it does, how it makes money, what could go right and wrong, and its profitability, growth, debt, and valuation. A beginner's checklist is generated at the end.
Expert opinion: This collection demonstrates the maturity of AI tools for fundamental analysis. However, it is important to remember: Claude is a powerful assistant, not a replacement for critical thinking. Final data verification and decision-making remain with the investor. This is especially relevant for the cryptocurrency market, where volatility and specific risks require additional human oversight.